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© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works This study shows the results of the SABINA H2020 project, which analyzes the effect of two level optimization algorithms to increase the consumption of renewable power sources and reduce greenhouse gas emissions. First, at building level, a building algorithm maximizes the self-consumption of generated energy by its own renewable power sources. Second, at district level, a market integrated district algorithm takes into account aspects related to the electricity grid, such as the electricity generation mix and the prices of electricity and ancillary services, and aggregates the energy flexibility forecast of buildings to minimize the overall CO 2 emissions while ensuring a cost reduction to prosumers Peer Reviewed

© 2020 Elsevier. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ The development of Urban-Scale Energy Modelling (USEM) at district or city level is today the goal of many research groups due to the increased interest in applications such as new strategies for city energy supply/demand, urban development planning, or distribution networks stability. It is believed that the assessment of the true potential for energy savings in a city can be done with computer simulation by considering a holistic analysis of the system. The goal of this paper is to provide a review of the existing USEM tools that aim at modelling the dynamic interaction among energy demand, generation and distribution in a city or district through the interaction of different sub-models. The main characteristics covered by the modelling tools are summarised in two matrices. The present study goes beyond other existing review studies by focusing on multi-domain USEM tools and emphasizing the distinction among the different architectures behind them. This work was supported by the research and innovation programme Horizon 2020 of the European Union under the Grant agreement no. 646456 (GrowSmarter); the GEIDI project (ref. TIN2016-78473-C3-3-R) financed by the Ministry of Economy and Competitiveness of Spain; and CC’s work was supported by the Grant IJCI-2015-26650 (MICINN). Objectius de Desenvolupament Sostenible::7 - Energia Assequible i No Contaminant Objectius de Desenvolupament Sostenible::11 - Ciutats i Comunitats Sostenibles Objectius de Desenvolupament Sostenible::7 - Energia Assequible i No Contaminant Objectius de Desenvolupament Sostenible::11 - Ciutats i Comunitats Sostenibles

Abstract The massive data centre energy consumption has motivated significant efforts to use energy efficiency strategies and the implementation of renewable energy sources that reduce their operational costs and environmental impact. Considering that the potential of many of these measures is often closely linked to the climate conditions, the location of data centres can have a major impact on their energy demand. Moreover, from a holistic approach, differences among regions become even more important when accounting for the electricity attributes from the grid. To assess these differences this work compares by the use of energy indicators the behaviour of a data centre located at different representative emplacements in Europe. To do so, a dynamic energy model which incorporates free cooling strategy and photovoltaic energy is developed. The paper concludes by suggesting that future data centre developments could consider site selection as a new strategy to limit the environmental impact attributable to this sector.

Model predictive controllers (MPC) have shown great potential for activating the energy flexibility of thermal loads, especially in buildings equipped with heat pump systems. In this work, an MPC controller is developed and tested within a co-simulation framework which couples an optimization software with a dynamic building simulation tool. The development phase is described in detail, in particular the methods to obtain simplified models to be used by the controller. The building envelope and the heat pump performance (based on experimental data) were thus modelled, both in heating and cooling seasons. Three different objective functions of the MPC are tested on a study case consisting of a Spanish residential building: promising results are obtained when the controller aims at minimizing operational costs (savings of 13–29%) or CO2 marginal emissions (savings of 19–29%). The development efforts, the required tuning and sensitivity of the MPC algorithm parameters, the adaptations needed between the cooling and heating operations are also discussed and put into perspective with the obtained benefits in terms of savings, comfort and load-shifting Peer Reviewed

There are international activities and on-going initiatives, particularly at the European level, to define what Positive Energy Districts should be, as the driving concept for the urban transition to a sustainable future. The first objective of the paper is to contribute to the on-going and lively debate about the definition of the notion of Sustainable Plus Energy Neighbourhood (SPEN), which highlights the multiple dimensions when talking about sustainability in districts moving beyond the traditional and strict building energy assessment. Based on a holistic methodology which ensures the consideration of the multidimensional nature and goals of SPEN, the paper outlines an evaluation framework. The evaluation framework defines the key performance indicators distributed in five categories that consider energy and power performance, GHG emissions, indoor environmental quality, smartness, flexibility, life cycle costs and social sustainability. This framework is designed to be implemented during integrated design processes aiming to select design options for a neighbourhood as well within during the operational phase for monitoring its performance. Further work will include the implementation and validation of the framework in four real-life positive energy neighbourhoods in different climate zones of Europe as part of syn.ikia H2020 project.

This study presents some preliminary results of an on-going European Project, RePublic-ZEB [1], where an analysis is conducted for identifying the cost optimal levels for the existing buildings, towards nearly Zero Energy Buildings (nZEB) performance. The analysis is applied to the reference building for an existing office building in five different countries: Italy, Portugal, Romania, Spain and Greece. The evaluation tool uses a new cost optimization procedure based on a sequential search-optimization technique considering discrete options [2] is applied and the results will be presented in terms of optimal "package of measures", energy consumption and global costs. Finally a cross-country analysis will be performed. © 2015 The Authors. Peer Reviewed